We validate our approaches on top of the state-of-the-art Transformer model [1]}. Experimental results on the benchmarks WMT14 English\(\Rightarrow \) German and English\(\Rightarrow \) French translation tasks show that exploiting sentential context consistently improves translation performance across language pairs.
Among the model variations, the deep strategies consistently outperform their shallow counterparts, which confirms our claim.
Linguistic analyses [2]} on the learned representations reveal that the proposed approach indeed provides richer linguistic information.
<FIGURE>